Google data extract using Dfp Api python using a GENERIC framework. Use the other script (exec_dfp.py) to download data from required api's.

Following the instructions in the below page and download the required library from google. https://github.com/googleads/googleads-python-lib

(work in progress...but as such the program should work without any issues)

Insert the client_id, client_secret, refresh_token, networkCode

from googleads import dfp, oauth2 oauth2_client = oauth2.GoogleRefreshTokenClient( client_id='THIS_IS_THE_CLIENT_ID_GENERATED_DURING_THE_OAUTH_PROCESS', client_secret='THIS_IS_CLIENT_SECRET', refresh_token='this_is_refresh_token_required_for_refreshing_access_token' ) client = dfp.DfpClient(oauth2_client, 'google_dfp_prod') networks = client.GetService('NetworkService').getAllNetworks() network = networks[0]['networkCode'] print "Network code : %s" % network client = dfp.DfpClient(oauth2_client,'google_dfp_prod', network)

The program uses config parser. hence the dfp_param.py is laid out such that config parser can read it.

1. This is the main program that executes. Currently the list of columns etc are all part of this. Once the program is completely built, the list of columns etc will be part of the dfp_param.py
2. There is an additional step in this program that does list iteration to rows. For example: secondarytrafficker_ids can be multiple. or salesperson_ids can be multiple. in that case, it will be a nested List within the dict object when we get the data from api. The program automatically converts that to multiple rows (normalize) repeating other columns.